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-matter interactions, development of automated AI/ML systems for novel materials processing and quality insurance. The lab combines additive manufacturing, large scale laser micro-processing, multiscale
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setups, large-scale data acquisition and analysis, FPGA programming skills, and knowledge of Python and C++ are important assets. The project is highly interdisciplinary (microtechnology/electronics
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learning (RL), such as (but not limited to) Theory of online learning, reinforcement learning, and data-driven control Learning in games, and multi-agent RL RLHF and alignment in LLMs Representation learning
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